The simulation of a transient leaching circuit
The hydrometallurgical leaching of sulphide concentrates was introduced in the 1950's. Generally the leaching mechanisms of these processes are not understood fundamentally. The reasons for this are the inherently complex nature of sulphide chemistry and that the sulphide concentrates usually consist of highly intergrown sulphide minerals. The leaching kinetics of sulphide concentrates where only one metal-sulphide mineral occurs have been investigated intensively, but not for sulphide concentrates with more than one metal-sulphide mineral. The behaviour of these mixed metal-sulphide minerals has mostly been investigated on plant scale to qualitatively determine the leaching trends of the process. The consequence of the relatively unKnown leaching mechanism and kinetics is that these processes are not controlled efficiently. This study was conducted on the acid-oxygen pressure leaching of Ni-Cu matte (the first stage leach process at the Ni-Cu refinery of Impala Platinum Ltd.). As a first step to improve the control efficiency of the process, the process must be stabilised. Therefore, an off line computer simulation program is proposed to control the repulping section of the plant that has previously been controlled solely by an operator. Controlling the repulping section is very important, because conditions exist in the repulping tanks for leaching to occur. This causes perturbations in the pulp entering the pressure leach autoclave. Due to the fast reaction kinetics of the matte in the pressure leach autoclave the perturbations entering the autoclave will influence the performance of the acid-oxygen pressure leach process. The simulation program was tested on the plant and indicated that considerable improvement in the stability of the operation could be achieved. In obtaining a better understanding of the behaviour of this process, it is essential that key variables and trends are identified. A methodology is proposed to analyse and model this ill-defined and poorly understood process from historical data by v artificial neural networks (ANN), inductive learning by decision trees and statistical techniques. The back propagation neural network, learning vector quantization neural network and the decision trees yielded comparable classification rates between 73% and 84%, and could serve as a basis for the adjustment of operating conditions to improve the efficiency of the process. The relative importance of the process variables is determined by a method of sensitivity analysis and together with the statistical mean, the effect of an increase or decrease in the variable on the process is quantified. These results are substantiated by experimental findings. A leaching mechanism for the acid-oxygen pressure leach of Ni-Cu matte is postulated. The leaching sequence of the nickel and copper sulphides is Ni3Sr Ni7S" NiS-Ni3S4, and CU2S-CU31SWCU1.BS-CUS, respectively. Ni7Sa and CU31 S1a are intermediate nickel and copper sulphide phases that form during the leaching process. Ni alloy has a galvanic effect on the sulphide minerals which inhibits the overall leaching rate and results in the formation of H2S and the intermediate nickel and copper sulphides (Ni7Sa and CU31 S1a). A semi-empirical kinetic model was developed based on the chemical reaction rate expressions of the leaching mechanism. This model can accurately simulate the batch leaching process for variations in the oxygen partial pressure, oxygen flowrate, temperature, particle size, initial acid concentration and pulp density. A sensitivity analysis on the model indicated that for a matte with a lower initial Ni alloy content the leaching rate of nickel is much faster.
Thesis (PhD (Process Engineeering))--University of Stellenbosch, 1995.